Website Personalization Based on Demographic Data

This study focuses on websites personalization based on user's demographic data. The main demographic data that used in this study are age, gender, race and occupation. These data is obtained through user profiling technique conducted during the study. Analysis of the data gathered is done to find the relationship between the user's demographic data and their preferences for a website design. These data will be used as a guideline in order to develop a website that will fulfill the visitor's need. The topic chose was Obesity. HCI issues are considered as one of the important factors in this study which are effectiveness and satisfaction. The methodologies used are website personalization process, incremental model, combination of these two methods and Cascading Style Sheet (CSS) which discussed detail in Chapter 3. After that, we will be discussing the effectiveness and evaluation of the personalization website that have been built. Last but not least, there will be conclusion that present the result of evaluation of the websites made by the respondents

Improved web page recommender system based on web usage mining

Web now becomes the backbone of the information. Today the major concerns are not the availability of information but rather obtaining the right information. Mining the web aims at discovering the hidden and useful knowledge from web hyperlinks, contents or usage logs.This paper focuses on improving the prediction of the next visited web pages and recommends them to the current anonymous user by assigning him to the best navigation profiles obtained by previous navigations of similar interested users.To represent the anonymous user’s navigation history, we used a window sliding method with size n over his current navigation session. Using CTI dataset the experimental results show higher prediction accuracy for the next visited pages for anonymous users compared to previous recommendation system

Web Mining for Web Personalization

Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user\u27s navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content, and user profile data. Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. In this article we present a survey of the use of Web mining for Web personalization. More specifically, we introduce the modules that comprise a Web personalization system, emphasizing the Web usage mining module. A review of the most common methods that are used as well as technical issues that occur is given, along with a brief overview of the most popular tools and applications available from software vendors. Moreover, the most important research initiatives in the Web usage mining and personalization areas are presented

A Survey on Personalized Recommendation Techniques

No Abstrac